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Development of monoclonal antibody-based blocking ELISA for detecting SARS-CoV-2 exposure in animals

Overview of attention for article published in mSphere, August 2023
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#28 of 2,264)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
25 news outlets
blogs
1 blog
twitter
3 X users
reddit
2 Redditors

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
11 Mendeley
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Title
Development of monoclonal antibody-based blocking ELISA for detecting SARS-CoV-2 exposure in animals
Published in
mSphere, August 2023
DOI 10.1128/msphere.00067-23
Pubmed ID
Authors

Fangfeng Yuan, Chi Chen, Lina M. Covaleda, Mathias Martins, Jennifer M. Reinhart, Drew R. Sullivan, Diego G. Diel, Ying Fang

Abstract

The global pandemic of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a significant threat to public health. Besides humans, SARS-CoV-2 can infect several animal species. Highly sensitive and specific diagnostic reagents and assays are urgently needed for rapid detection and implementation of strategies for prevention and control of the infection in animals. In this study, we initially developed a panel of monoclonal antibodies (mAbs) against SARS-CoV-2 nucleocapsid protein. To detect SARS-CoV-2 antibodies in a broad spectrum of animal species, an mAb-based blocking enzyme-linked immunosorbent assay (bELISA) was developed. Test validation using a set of animal serum samples with known infection status obtained an optimal percentage of inhibition cut-off value of 17.6% with diagnostic sensitivity of 97.8% and diagnostic specificity of 98.9%. The assay demonstrates high repeatability as determined by a low coefficient of variation (7.23%, 4.89%, and 3.16%) between-runs, within-run, and within-plate, respectively. Testing of samples collected over time from experimentally infected cats showed that the bELISA was able to detect seroconversion as early as 7 days post-infection. Subsequently, the bELISA was applied for testing pet animals with coronavirus disease 2019 (COVID-19)-like symptoms and specific antibody responses were detected in two dogs. The panel of mAbs generated in this study provides a valuable tool for SARS-CoV-2 diagnostics and research. The mAb-based bELISA provides a serological test in aid of COVID-19 surveillance in animals. IMPORTANCE Antibody tests are commonly used as a diagnostic tool for detecting host immune response following infection. Serology (antibody) tests complement nucleic acid assays by providing a history of virus exposure, no matter symptoms developed from infection or the infection was asymptomatic. Serology tests for COVID-19 are in high demand, especially when the vaccines become available. They are important to determine the prevalence of the viral infection in a population and identify individuals who have been infected or vaccinated. ELISA is a simple and practically reliable serological test, which allows high-throughput implementation in surveillance studies. Several COVID-19 ELISA kits are available. However, they are mostly designed for human samples and species-specific secondary antibody is required for indirect ELISA format. This paper describes the development of an all species applicable monoclonal antibody (mAb)-based blocking ELISA to facilitate the detection and surveillance of COVID-19 in animals.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 27%
Student > Master 1 9%
Professor 1 9%
Professor > Associate Professor 1 9%
Student > Postgraduate 1 9%
Other 0 0%
Unknown 4 36%
Readers by discipline Count As %
Veterinary Science and Veterinary Medicine 2 18%
Agricultural and Biological Sciences 2 18%
Biochemistry, Genetics and Molecular Biology 2 18%
Environmental Science 1 9%
Unknown 4 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 196. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 November 2023.
All research outputs
#208,988
of 25,990,612 outputs
Outputs from mSphere
#28
of 2,264 outputs
Outputs of similar age
#4,007
of 361,196 outputs
Outputs of similar age from mSphere
#2
of 40 outputs
Altmetric has tracked 25,990,612 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,264 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.3. This one has done particularly well, scoring higher than 98% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 361,196 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.